Clinical Cardiology最新文献

Recognizing that acute coronary syndromes (ACSs) constitute a spectrum encompassing unstable angina, non-ST elevation myocardial infarction (NSTEMI), and ST elevation myocardial infarction (STEMI), the 2023 European Society of Cardiology Guidelines [1] for the management of ACSs addressed all three. This differs from the prior US guidelines that individually addressed unstable angina, NSTEMI, and STEMI. The 2023 ESCACS Guidelines thus encompass comprehensive patient management from admission to long-term care, again including what in prior US guidelines would have been a secondary prevention guideline. In addition, the task force included a patient member who provided a patient perspective that is highlighted in the European publication.

Because 80% of both women and men with ACS present with chest pain or pressure, this symptom is detailed in the guidelines, derived in part from the US Chest Pain guideline [2]. The ESC document noted that additional symptoms such as diaphoresis, indigestion or epigastric pain, and shoulder or arm pain occur commonly in both women and men with an ACS. However, some symptoms appear to be more common in women, including dizziness and syncope, nausea and vomiting, jaw and back pain, shortness of breath, pain between the shoulder blades, palpitations, and fatigue.

In advancing the science and implementation, the 2023 Guidelines offer a conceptual approach of five items: think A.C.S. at the initial assessment, think invasive management, think antithrombotic therapy, think revascularization, and think secondary prevention. To further explain the thinking A.C.S. at the initial evaluation of patients with suspected ACS, “A” relates to an abnormal ECG (performing an ECG urgently to assess for evidence of ischemia or other abnormalities), “C” considers the clinical context and other available investigations, and “S” for stable, performing an examination to assess whether the patient is clinically and vitally stable.

The guidelines (Figure 1) graphically explore the spectrum of clinical presentations such that the patient may initially have had chest pain, but at presentation either has minimal or no symptoms; to the patient with increasing chest pain or other symptoms; to the patient with persistent chest pain or symptoms; to the patient with cardiogenic shock or acute heart failure; and finally, the patient who presents with a cardiac arrest. The ECG may be normal at presentation, may have ST segment depression as potentially an NSTEMI, or may have ST segment elevation leading to the immediate diagnosis of STEMI. If the high-sensitivity troponin [3] is not elevated, the resultant diagnosis is unstable angina, but the characteristic rise and fall of high-sensitivity troponin does not differentiate between NSTEMI and STEMI.

As noted, the initial ACS assessment includes the electrocardiogram, physical examination, clinical history, vital signs, and high-sensit

We read with great interest this observational cohort study with a median duration of 4 years by Boos et al. [1]. In this study, ambulatory arterial stiffness index (AASI) was found to be an independent predictor of the development of AF [1]. First of all, we would like to congratulate the authors of this article for raising awareness that parameters (such as AASI) obtained from ambulatory blood pressure monitoring (ABPM) have independent predictive value in many important diseases [2, 3]. We thought some points should be clarified so we decided to add some helpful comments on this article.

It is known that the diagnosis duration of patients with diseases like hypertension, heart failure, and diabetes may affect AASI, which provides information about arterial stiffness [3, 4]. Therefore, was there a statistically significant difference between the diagnosis duration of these diseases (hypertension, heart failure, and diabetes) in the AF and non-AF groups?

In addition, the incidence of heart failure and ischemic stroke was higher in the AF group in the study. We know that these diseases have an impact on AASI [2]. Therefore, we think that it would be appropriate to include these diseases as confounding variables in the Cox regression analysis. The authors said that they limited the number of variables included in the regression model because the AF incidence was 9.1% (n = 75). However, in regression analysis, the number of events per variable can be between 5–9. It is known that the results of this analysis are correct [5]. Therefore, the number of variables evaluated in the regression analysis could have been increased to eight. Finally, the difference in β-blocker use rates between groups may have caused AASI to lead to a statistically significant difference between the groups. Purifying the study results from the effects of the drugs used would also enable better interpretation of the results.

Despite these comments, we agree that this study will contribute greatly to the literature.

The authors declare no conflicts of interest.